Best Data Engineering Tools for Apache Kafka

RudderStack is the smart customer information pipeline. You can easily build pipelines that connect your entire customer data stack. Then, make them smarter by pulling data from your data warehouse to trigger enrichment in customer tools for identity sewing and other advanced uses cases. Start building smarter customer data pipelines today.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

Answer questions today, not next week. Latitude makes it easy to create low-code data apps within minutes. You don't need a data stack, but you can help your team answer data-related questions. Connect your data sources to Latitude and you can immediately start exploring your data. Latitude connects with your database, data warehouse, or other tools used by your team. Multiple sources can be used in the same analysis. We support over 100 data sources. Latitude offers a vast array of data sources that can be used by teams to explore and transform data. This includes using our AI SQL Assistant, visual programming, and manually writing SQL queries. Latitude combines data exploration with visualization. You can choose from tables or charts and add them to the canvas you are currently working on. Interactive views are easy to create because your canvas already knows how variables and transformations work together.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Mozart Data is the all-in-one modern data platform for consolidating, organizing, and analyzing your data. Set up a modern data stack in an hour, without any engineering. Start getting more out of your data and making data-driven decisions today.

Ascend provides data teams with a unified platform that allows them to ingest and transform their data and create and manage their analytics engineering and data engineering workloads. Ascend is supported by DataAware intelligence. Ascend works in the background to ensure data integrity and optimize data workloads, which can reduce maintenance time by up to 90%. Ascend's multilingual flex-code interface allows you to use SQL, Java, Scala, and Python interchangeably. Quickly view data lineage and data profiles, job logs, system health, system health, and other important workload metrics at a glance. Ascend provides native connections to a growing number of data sources using our Flex-Code data connectors.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

Your offline data can be used to make real-time predictions, without the need for custom pipelines. Data consistency is achieved between offline training and online prediction, eliminating train-serve bias. Standardize data engineering workflows within a consistent framework. Feast is used by teams to build their internal ML platforms. Feast doesn't require dedicated infrastructure to be deployed and managed. Feast reuses existing infrastructure and creates new resources as needed. You don't want a managed solution, and you are happy to manage your own implementation. Feast is supported by engineers who can help with its implementation and management. You are looking to build pipelines that convert raw data into features and integrate with another system. You have specific requirements and want to use an open-source solution.

Kestra is a free, open-source orchestrator based on events that simplifies data operations while improving collaboration between engineers and users. Kestra brings Infrastructure as Code to data pipelines. This allows you to build reliable workflows with confidence. The declarative YAML interface allows anyone who wants to benefit from analytics to participate in the creation of the data pipeline. The UI automatically updates the YAML definition whenever you make changes to a work flow via the UI or an API call. The orchestration logic can be defined in code declaratively, even if certain workflow components are modified.

Molecula, an enterprise feature store, simplifies, speeds up, and controls big-data access to power machine scale analytics and AI. Continuously extracting features and reducing the data dimensionality at the source allows for millisecond queries, computations, and feature re-use across formats without copying or moving any raw data. The Molecula feature storage provides data engineers, data scientists and application developers with a single point of access to help them move from reporting and explaining with human scale data to predicting and prescribing business outcomes. Enterprises spend a lot of time preparing, aggregating and making multiple copies of their data before they can make any decisions with it. Molecula offers a new paradigm for continuous, real time data analysis that can be used for all mission-critical applications.

The largest global team of Fast Data and Functional Programming engineers focused on developing high-performance, customized solutions. Through rapid prototyping and proof-of-concept, we move from "thought to thing". CI/CD can help you create an ecosystem that will deliver at scale. To develop a shared vision, it is important to understand the stakeholder needs and the strategic intent. MVP should be deployed to launch the product in a most efficient and expedient manner. Continuous improvements and enhancements are made to meet new requirements. Without the ability to use the most recent tools and technology, it would be impossible to build great products or provide unmatched engineering services. We help you capitalize on opportunities, respond effectively to competitive threats, scale successful investments, and reduce organizational friction in your company's processes, structures, and culture. Knoldus assists clients in identifying and capturing the highest value and meaningful insights from their data.

witboost allows your company to become data-driven, reduce time-to market, it expenditures, and overheads by using a modular, scalable and efficient data management system. There are a number of modules that make up witboost. These modules are building blocks that can be used as standalone solutions to solve a specific problem or to create the ideal data management system for your company. Each module enhances a specific function of data engineering and can be combined to provide the perfect solution for your specific needs. This will ensure a fast and seamless implementation and reduce time-to market, time-to value and, consequently, the TCO of your data engineering infrastructure. Smart Cities require digital twins to anticipate needs and avoid unforeseen issues, gather data from thousands of sources, and manage telematics that is ever more complicated.